. 2018 Apr;33(4):381-392.

doi: 10.1007/s10654-017-0346-8. Epub 2017 Dec 20.

Utility of inverse probability weighting in molecular pathological epidemiology

Li Liu^{1

2

3

4}, Daniel Nevo^{5

6}, Reiko Nishihara^{2

3

6

7}, Yin Cao^{2

8

9}, Mingyang Song^{2

8

9}, Tyler S Twombly¹, Andrew T Chan^{7

8

9

10}, Edward L Giovannucci^{2

6

10}, Tyler J VanderWeele^{5

6}, Molin Wang^{11

12

13}, Shuji Ogino^{14

15

16

17}

Affiliations

¹ Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
² Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
³ Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA.
⁴ Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
⁵ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02215, USA.
⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA.
⁹ Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
¹⁰ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02215, USA. stmow@channing.harvard.edu.
¹² Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. stmow@channing.harvard.edu.
¹³ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. stmow@channing.harvard.edu.
¹⁴ Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA. shuji_ogino@dfci.harvard.edu.
¹⁵ Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA. shuji_ogino@dfci.harvard.edu.
¹⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. shuji_ogino@dfci.harvard.edu.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. shuji_ogino@dfci.harvard.edu.

PMID: 29264788
PMCID: PMC5948129
DOI: 10.1007/s10654-017-0346-8

Utility of inverse probability weighting in molecular pathological epidemiology

Li Liu et al. Eur J Epidemiol. 2018 Apr.

. 2018 Apr;33(4):381-392.

doi: 10.1007/s10654-017-0346-8. Epub 2017 Dec 20.

Authors

Affiliations

¹ Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
² Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
³ Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA.
⁴ Department of Epidemiology and Biostatistics, and the Ministry of Education Key Lab of Environment and Health, School of Public Health, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
⁵ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02215, USA.
⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁸ Division of Gastroenterology, Massachusetts General Hospital, Boston, MA, USA.
⁹ Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
¹⁰ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
¹¹ Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Ave., Boston, MA, 02215, USA. stmow@channing.harvard.edu.
¹² Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. stmow@channing.harvard.edu.
¹³ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. stmow@channing.harvard.edu.
¹⁴ Department of Oncologic Pathology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA. shuji_ogino@dfci.harvard.edu.
¹⁵ Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, 450 Brookline Ave., Room SM1036, Boston, MA, 02215, USA. shuji_ogino@dfci.harvard.edu.
¹⁶ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. shuji_ogino@dfci.harvard.edu.
¹⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. shuji_ogino@dfci.harvard.edu.

PMID: 29264788
PMCID: PMC5948129
DOI: 10.1007/s10654-017-0346-8

Abstract

As one of causal inference methodologies, the inverse probability weighting (IPW) method has been utilized to address confounding and account for missing data when subjects with missing data cannot be included in a primary analysis. The transdisciplinary field of molecular pathological epidemiology (MPE) integrates molecular pathological and epidemiological methods, and takes advantages of improved understanding of pathogenesis to generate stronger biological evidence of causality and optimize strategies for precision medicine and prevention. Disease subtyping based on biomarker analysis of biospecimens is essential in MPE research. However, there are nearly always cases that lack subtype information due to the unavailability or insufficiency of biospecimens. To address this missing subtype data issue, we incorporated inverse probability weights into Cox proportional cause-specific hazards regression. The weight was inverse of the probability of biomarker data availability estimated based on a model for biomarker data availability status. The strategy was illustrated in two example studies; each assessed alcohol intake or family history of colorectal cancer in relation to the risk of developing colorectal carcinoma subtypes classified by tumor microsatellite instability (MSI) status, using a prospective cohort study, the Nurses' Health Study. Logistic regression was used to estimate the probability of MSI data availability for each cancer case with covariates of clinical features and family history of colorectal cancer. This application of IPW can reduce selection bias caused by nonrandom variation in biospecimen data availability. The integration of causal inference methods into the MPE approach will likely have substantial potentials to advance the field of epidemiology.

Keywords: Etiologic heterogeneity; Marginal structural model; Missing at random; Neoplasm; Selection bias; Unique disease principle.

PubMed Disclaimer

Conflict of interest statement

Conflict of interest: The authors declare that they have no conflicts of interest.

Figures

**Fig. 1**
Simplified diagram showing how inverse probability weighting (IPW) balances the selection bias in subtype analysis. (a) subtype analysis without IPW; (b) subtype analysis incorporated with IPW. Y₁: subtype 1; Y₂: subtype 2; X: exposures (alcohol intake, family history of colorectal cancer, et al.); Z: confounders; Q: clinical features (tumor stage, tumor location, tumor differentiation, et al.); U: unobserved variables; O: subtype availability

See this image and copyright information in PMC

Cited by

Flavonoid intake and survival after diagnosis of colorectal cancer: a prospective study in 2 US cohorts.
Shi S, Wang K, Zhong R, Cassidy A, Rimm EB, Nimptsch K, Wu K, Chan AT, Giovannucci EL, Ogino S, Ng K, Meyerhardt JA, Song M. Shi S, et al. Am J Clin Nutr. 2023 Jun;117(6):1121-1129. doi: 10.1016/j.ajcnut.2023.03.026. Epub 2023 Apr 1. Am J Clin Nutr. 2023. PMID: 37011765 Free PMC article.
Long-term yogurt intake and colorectal cancer incidence subclassified by Bifidobacterium abundance in tumor.
Ugai S, Liu L, Kosumi K, Kawamura H, Hamada T, Mima K, Arima K, Okadome K, Yao Q, Matsuda K, Zhong Y, Mizuno H, Chan AT, Garrett WS, Song M, Giannakis M, Giovannucci EL, Zhang X, Ogino S, Ugai T. Ugai S, et al. Gut Microbes. 2025 Dec;17(1):2452237. doi: 10.1080/19490976.2025.2452237. Epub 2025 Feb 12. Gut Microbes. 2025. PMID: 39937126 Free PMC article.
An integrated analysis of lymphocytic reaction, tumour molecular characteristics and patient survival in colorectal cancer.
Haruki K, Kosumi K, Li P, Arima K, Väyrynen JP, Lau MC, Twombly TS, Hamada T, Glickman JN, Fujiyoshi K, Chen Y, Du C, Guo C, Väyrynen SA, Dias Costa A, Song M, Chan AT, Meyerhardt JA, Nishihara R, Fuchs CS, Liu L, Zhang X, Wu K, Giannakis M, Nowak JA, Ogino S. Haruki K, et al. Br J Cancer. 2020 Apr;122(9):1367-1377. doi: 10.1038/s41416-020-0780-3. Epub 2020 Mar 11. Br J Cancer. 2020. PMID: 32157241 Free PMC article.
Coffee Intake and Colorectal Cancer Incidence According to T-Cell Response.
Ugai T, Haruki K, Väyrynen JP, Zhong R, Borowsky J, Fujiyoshi K, Lau MC, Zhao M, Akimoto N, Chang TW, Kishikawa J, Arima K, Shi SS, Gu S, Fuchs CS, Giovannucci EL, Giannakis M, Zhang X, Song M, Meyerhardt JA, Wang M, Nowak JA, Ogino S. Ugai T, et al. JNCI Cancer Spectr. 2020 Sep 7;4(6):pkaa068. doi: 10.1093/jncics/pkaa068. eCollection 2020 Dec. JNCI Cancer Spectr. 2020. PMID: 33409450 Free PMC article.
Vitamin C intake and colorectal cancer survival according to KRAS and BRAF mutation: a prospective study in two US cohorts.
Shi S, Wang K, Ugai T, Giannakis M, Cazaubiel J, Chan AT, Giovannucci EL, Nowak JA, Meyerhardt JA, Ogino S, Song M. Shi S, et al. Br J Cancer. 2023 Nov;129(11):1793-1800. doi: 10.1038/s41416-023-02452-2. Epub 2023 Sep 30. Br J Cancer. 2023. PMID: 37775523 Free PMC article.

See all "Cited by" articles

References

1. Ogino S, Lochhead P, Chan AT, Nishihara R, Cho E, Wolpin BM, Meyerhardt JA, Meissner A, Schernhammer ES, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of epigenetics: emerging integrative science to analyze environment, host, and disease. Mod Pathol. 2013;26(4):465–84. - PMC - PubMed
1. Ogino S, Nishihara R, VanderWeele TJ, Wang M, Nishi A, Lochhead P, Qian ZR, Zhang X, Wu K, Nan H, Yoshida K, Milner DA, Jr, Chan AT, Field AE, Camargo CA, Jr, Williams MA, Giovannucci EL. Review Article: The Role of Molecular Pathological Epidemiology in the Study of Neoplastic and Non-neoplastic Diseases in the Era of Precision Medicine. Epidemiology. 2016;27(4):602–11. - PMC - PubMed
1. Nishihara R, VanderWeele TJ, Shibuya K, Mittleman MA, Wang M, Field AE, Giovannucci E, Lochhead P, Ogino S. Molecular pathological epidemiology gives clues to paradoxical findings. Eur J Epidemiol. 2015;30(10):1129–35. - PMC - PubMed
1. Nishi A, Milner DA, Jr, Giovannucci EL, Nishihara R, Tan AS, Kawachi I, Ogino S. Integration of molecular pathology, epidemiology and social science for global precision medicine. Expert Rev Mol Diagn. 2016;16(1):11–23. - PMC - PubMed
1. Ogino S, Chan AT, Fuchs CS, Giovannucci E. Molecular pathological epidemiology of colorectal neoplasia: an emerging transdisciplinary and interdisciplinary field. Gut. 2011;60(3):397–411. - PMC - PubMed

Publication types

Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Utility of inverse probability weighting in molecular pathological epidemiology

Affiliations

Utility of inverse probability weighting in molecular pathological epidemiology

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical

Research Materials

Abstract

Conflict of interest statement

Figures

Similar articles

Cited by

References

Publication types

MeSH terms

Substances

Related information

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical

Research Materials